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Seasonal dynamics and diversity of bacteria in retail oyster tissues
International Journal of Food Microbiology 173 (2014) 14–20
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International Journal of Food Microbiology journal homepage: www.elsevier.com/locate/ijfoodmicro
Seasonal dynamics and diversity of bacteria in retail oyster tissues Dapeng Wang ⁎, Qian Zhang, Yan Cui, Xianming Shi MOST-USDA Joint Research Center for Food Safety & Bor Luh Food Safety Center, School of Agriculture and Biology & State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai 200240, PR China
a r t i c l e
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Article history: Received 14 October 2013 Received in revised form 6 December 2013 Accepted 8 December 2013 Available online 19 December 2013 Keywords: Retail oyster Tissues DGGE Seasonal dynamics Bacterial diversity
a b s t r a c t Oysters are one of the important vehicles for the transfer of foodborne pathogens. It was reported that bacteria could be bio-accumulated mainly in the gills and digestive glands. In artificially treated oysters, bacterial communities have been investigated by culture-independent methods after harvest. However, little information is available on the seasonal dynamics of bacterial accumulation in retail oyster tissues. In this study, retail oysters were collected from local market in different seasons. The seasonal dynamics and diversity of bacteria in oyster tissues, including the gills, digestive glands and residual tissues, were analyzed by denaturing gradient gel electrophoresis (DGGE). It was interesting that the highest bacterial diversity appeared in the Fall season, not in summer. Our results indicated that Proteobacteria was the predominant member (23/46) in oyster tissues. Our results also suggested that bacterial diversity in gills was higher than that in digestive glands and other tissues. In addition, not all the bacteria collected from surrounding water by gills were transferred to digestive glands. On the other hand, few bacteria were found in oyster tissues except in the gills. Therefore, the gills could be the best candidate target tissue for monitoring of pathogenic bacteria either to human or to oyster. © 2013 Elsevier B.V. All rights reserved.
1. Introduction Oysters are filter feeders. Because of this character, oysters bioaccumulate almost all kinds of particles, which exist in surrounding water, including bacteria and viruses. Some of them can cause infections with serious consequences either in human consumers or in oysters (Green, Barnes, 2010; Romero et al., 2002; Wang and Shi, 2011). Therefore, most literatures focused on the detection of those pathogens in oysters (Green and Barnes, 2010; Liu et al., 2012; Nordstrom et al., 2007). The microflora present in oysters depends on the environmental conditions (Kenneth et al., 2009; Prapaiwong et al., 2009).After harvest, bacterial communities, including pathogenic bacteria, in oyster would be changed dramatically even during refrigeration (Chen et al., 2013; Fernandez-Piquer et al., 2012; Gooch et al., 2002). It was reported that the total aerobic bacteria counts were over 107 CFU/g in autumn after 1 week storage at 4 °C (Prapaiwong et al., 2009). Therefore, the dynamics of bacterial diversity was a concerned issue. In general, culture-based assay was standard for detection of bacteria in oyster, but, it was not good enough to evaluate the bacterial diversity in oysters (Broekaert et al., 2011; Fernandez-Piquer et al., 2012). It was reported that less bacteria could be cultured using the currently available methods (Kenneth et al., 2009; Romero et al., 2002). Therefore, culture-independent methods were widely used to reveal the bacterial
⁎ Corresponding author at: 800 Dongchuan Rd. Minhang, Shanghai 200240, PR China, Tel.: +86 21 34206613; fax: +86 21 34206616. E-mail addresses: [email protected], [email protected] (D. Wang). 0168-1605/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ijfoodmicro.2013.12.008
communities in oyster tissues. In this field, many culture-independent methods were applied to evaluate the bacterial diversity, including denaturing gradient gel electrophoresis (DGGE), fluorescent in situ hybridization (FISH),terminal restriction fragment length polymorphism (T-RFLP) and automated ribosomal intergenic spacer analysis (ARISA) (Chen et al., 2013; Fernandez-Piquer et al., 2012; Hernandez-Zarate, Olmos-Soto, 2006; Zurel et al., 2011). In all these methods, DGGE was perhaps the most commonly used in the culture-independent fingerprinting techniques (Broekaert et al., 2011; Chen et al., 2013), and it was widely used for detection of microbes in food (Broekaert et al., 2011; Ercolini, 2004; Kenneth et al., 2009; Li et al., 2012). Recently, tissues from oysters were investigated to look for the bacterial diversities, such as live oyster (Azandegbe et al., 2012; FernandezPiquer et al., 2012; Kenneth et al., 2009), digestive glands (Green and Barnes, 2010; King et al., 2012), and the gills (Chen et al., 2013; Hernandez-Zarate et al., 2006; Zurel et al., 2011). Generally, the oysters were collected from aquatic farms and analyzed after different artificial treatments, including different storage temperature, high-pressure, quick-frozen, and infection with parasites as mentioned above. Those data boarded our knowledge on the bacterial diversity in oyster tissues. However, it was reported that oysters collected directly in the wild and laboratory-based might have different bacterial communities (Kenneth et al., 2009; Thompson et al., 2005; Trabal et al., 2012). So far, less information was available on bacterial diversities in retail oysters. To address this issue, this study investigated the seasonal dynamics and diversities of bacteria in retail oysters during transport and storage processes. This study was designed to: (1) investigate the changes of communities in different seasons; (2) reveal the diversities of bacterial communities in different retail oyster tissues. The results would provide
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more information and would be valuable as an analog of profiling on the diversities of bacteria in retail oysters. 2. Material and methods 2.1. Oyster sample treatments Oysters (Crassostrea gigas) were collected randomly from Jiangyang market in Shanghai in 2011. The oysters were collected for analysis after shipping to the market. Oysters were stored with ice in boxes. The information of samples was listed in Table 1 and treated as previously described (Wanget al., 2010a, 2010b). Briefly, oysters (n = 20) were collected randomly and opened with sterilized knives. Different tissues were dissected, including the gills, digestive glands (stomach, gut and digestive diverticula) and residual tissues (mantle and adductor muscle). Each tissue (50.0 g) was mixed with 200 ml (1:4) sterile physiological saline, and homogenized in sterile grinders. All tissues were grounded at 12,000 rpm for 1 min. After treatment, all supernatants (0.5 ml) were stored in 20% (final concentration) sterile glycerol at −80 °C until further use. 2.2. Extraction of genomic DNA The pre-treated supernatants (0.2 mL) were vortexed and centrifuged at 10,000 rpm (Eppendorf 5814D, Hamburg, Germany) for 5 min. The precipitates were washed twice with sterile physiological salt (1.0 mL) and resuspended in 0.1 mL sterile physiological salt. Genomic DNA was extracted with Allmag™ Blood Genomic DNA kit (Allrun, Shanghai, China) according to the manufacturer's protocol. Finally, genomic DNA eluted with 50 μL elution buffer was stored at −80 °C until further use.
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60 s, primer annealing at 55 °C for 45 s, and primer extension at 72 °C for 60 s; then final extension at 72 °C for 10 min. The PCR products were visualized in a 1.5% agarose gel. All PCR reactions were repeated separately for three times. To avoid bias, triplicate production of PCR was pooled, which amplified from each sample. Then, DNA was recovered with DNA Gel Extraction Kit (Omega Bio-Tek, Inc., USA) according to the manufacturer's protocol. 2.4. Denaturing gradient gel electrophoresis DGGE analysis was performed on Dcode universal mutation detection system (Bio-Rad, USA) as previously described (Muyzer et al., 1993) with minor modifications. Briefly, 10.0 μL purified PCR product was loaded to an 8% (wt/vol) polyacrylamide gel in TAE buffer. Optimal electrophoresis experiments were performed at 60 °C by using gels containing a linear 35%–55% denaturant gradient (100% corresponding to 7 mol/L urea and 40% acrylamide). Electrophoresis was performed at a constant voltage of 150 V for 5 h. Following electrophoresis, the gels were preceded for silver staining. The solutions used were 1.0% (vol/vol) ethanol plus 0.5% (vol/vol) acetic acid for fixation for 15 min; wash with filtered water (Milli-Q, Millipore) for 2 times; 0.2% silver nitrate (wt/vol) for staining for 15 min, freshly prepared stain solution containing 0.15% (vol/vol) formaldehyde; wash with filtered water for 2 times; 1.5% NaOH for developing for 5–7 min, freshly prepared developing solution containing 0.5% (vol/vol) formaldehyde; finally, 10.0% (vol/vol) ethanol and 0.5% (vol/vol) acetic acid to stop the development. The gels were digitalized and analyzed with the software package Quantity One Ver. 4.6.2 program (Bio-Rad, USA). The virtual DGGE image was performed to create a virtual DGGE image and recorded the bands in each lane. 2.5. Second amplification and sequencing
2.3. Amplification of 16S rRNA genes The V3-region of 16S rRNA genes was amplified by Polymerase Chain Reaction (PCR) in a PTC-200 thermocycler (MJ research, CA, USA). The bacterial DNA from different tissues was amplified using GC338F and 518R primers. The PCR mix consisted of 2.0 μL of genomic DNA, 2.0 U TaqE (Fermentas, Fisher Scientific, USA), 5.0 μL PCR buffer (with Mg2+), 3.2 μL of 2.5 mmol/L dNTPs, 1.0 μL of 20.0 μmol/L primers (GC338F: 5′- CCTACGGGAGGCAGCAG −3′ and 518R: 5′- ATTACCGCGG CTGCTGG-3′), the GC clamp sequence is 5′-CGCCCGGGGCGCG CCCCGG GGCGGGGCGGGGGCGCGGGGGG-3′ (Muyzer et al., 1993) and deionized water to bring up to a total reaction volume of 50.0 μL. The cycling conditions were as follows: initial denaturation at 94 °C for 5 min; 30 cycles consisting of template denaturation at 94 °C for
The bands were excised from DGGE gel and eluted in ultra pure water. DNA was recovered with Poly-Gel Extraction Kit (Omega Bio-Tek, Inc., USA) according to the manufacturer's protocol. The V3-region genes were amplified again using 338F and 518R primers (Muyzer et al., 1993). The PCR mix consisted of 2.0 μL of recovered DNA, 2.0 U TaqE (Fermentas, Fisher Scientific, USA), 5.0 μL PCR buffer (with Mg2+), 3.2 μL of 2.5 mmol/L dNTPs, 1.0 μL of 20.0 μmol/L primers and deionized water to bring up to a total reaction volume of 50.0 μL. The cycling conditions were as follows: initial denaturation at 94 °C for 4 min; 30 cycles consisting of template denaturation at 94 °C for 30 s, primer annealing at 55 °C for 30 s, and primer extension at 72 °C for 30 s; then final extension at 72 °C for 10 min. The PCR products were visualized in a 1.5% agarose gel.
Table 1 Sample information and relative species diversity (H), evenness (E), and richness (S) estimates from analysis of the DGGE band profiles of retail oyster samples. Sample
Shannon–Wiener Index (H)
Evenness (E)
Richness (S)
Seasons (Month)
Tissues
I II III IV V VI VII VIII IX X XI XII XIII XIV XV
3.019 2.924 2.815 3.407 2.982 2.904 2.986 2.886 2.657 2.907 2.874 2.886 2.923 2.650 2.992
0.938 0.960 0.925 0.943 0.951 0.926 0.952 0.920 0.938 0.915 0.904 0.920 0.932 0.917 0.929
25 21 21 37 23 23 23 23 17 24 24 23 23 18 25
Spring (Apr.) Early Summer (Jun.) Later Summer (Aug.) Fall (Nov.) Winter (Jan.) Spring (Apr.) Early Summer (Jun.) Later Summer (Aug.) Fall (Nov.) Winter (Jan.) Spring (Apr.) Early Summer (Jun.) Later Summer (Aug.) Fall (Nov.) Winter (Jan.)
Gills
Digestive glands
Residual tissues
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The isolated amplicons were recovered with DNA Gel Extraction Kit (Omega Bio-Tek, Inc., USA) and cloned into the pMD18-T (TaKaRa, Dalian, China) according to the protocol provided by the kit. Following incubation, the ligation products were transformed into Escherichia coli DH5α competent cells and plated onto Luria-Bertani (LB, OXIOD, Ltd, England) agar plates with 50 μg/mL ampicillin (Sigma, MO, USA), X-gal and isopropyl β-D-1-thiogalactopyranoside. After16 h incubation at 37 °C, the 3 white clones were selected randomly, and sequenced by Beijing Yiming Fuxing Biotechnology Co. 2.6. Statistical and phylogenetic analysis The Shannon–Wiener index and Evenness (equitability) were calculated using the equations from Krebs (Krebs., 1989). The richness was estimated as described by Oguntoyinbo (Oguntoyinbo et al., 2011). Sequences were initially compared to the available database using BLAST (Basic Local Alignment Search Tool) to determine their approximate phylogenetic affiliations and orientation. Sequences were aligned with reference 16S rRNA sequences from GenBank using the computer software program MEGA Ver. 5.0 (www.megasoftware.net). Phylogenetic trees were constructed by the neighbor-joining distance method (bootstrap =1000). 2.7. Nucleotide sequence accession numbers Nucleotide sequences obtained in this study were submitted to the NCBI GenBank database with the accession numbers of KF633394– KF633439. 3. Results 3.1. DGGE analysis of V3 regions The V3 regions of 16S rRNA from different species amplified from purified genomic DNA by PCR were separated in DGGE profiles. Total
Digestive glands
Gills I
II
III
IV
V
VI VII VIII IX
Residual tissues X
XI
XII XIII XIV XV
of 46 different bands were observed in the DGGE gel (Fig. 1). All of the bands were recovered and sequenced after second round PCR. The differences and changes in bacterial communities in oyster tissues were clearly observed (Figs. 1 and 2). There was significant difference among the three parts of tissues (Figs. 1 and 2). When the bands were analyzed according to different tissues, the results indicated that almost all bacteria were present in the gills; some were transferred from the gills to digestive glands (Fig. 2).In Fall season, bands 27 and 28 were obvious in digestive glands and residual tissues, while they were not obvious in the gills (Fig. 1).Meanwhile, not all bacteria, which were bio-accumulated by the gills, could be transferred to other tissues (Fig. 2). On the other hand, many bands were only shown in the gills, such as, bands 4, 5, 9 (Fig. 2). The bacterial diversity in the gills was highest compared with other tissues in every season (Figs. 1 and 2). In the Fall season, there were 31 bands present in the gills (lane 4 in Fig. 1), while only 14 bands were observed in residual tissues (lane 14 in Fig. 1). In digestive glands, the bacterial diversity seemed to be the same in different seasons except in the Fall season (Fig. 1). From Fig. 2, 22 bands always appeared in the different tissues. Most of them (12/22) were grouped into Proteobacteria (Supplementary Table 1). The bacterial diversity in the digestive glands (25 bands) was the lowest in all tissues samples. The highest diversity was in the gills (45 bands). There were some bands that appeared in two parts of tissues. According to time course, the bacterial diversity in Fall season was the highest in the whole year with 36 bands detected in DGGE (Fig. 3). Summer followed with 31 bands (Fig. 3), and 28 bands in early summer and 26 bands in later summer respectively (Supplementary Table 1).On the other hand, in winter, there were only 23 bands appearing in different tissues (Fig. 3). From Fig. 3, 16 bands always appeared in the different seasons. Most of them (9/16) were also grouped into Proteobacteria (Supplementary Table 1). In addition, all of the 16 bands always appeared in the different tissues (Figs. 2 and 3).The bacterial diversity in the winter season (23 bands) was the lowest in all oyster samples. The highest diversity was in the Fall season (36 bands). There were a couple of bands that appeared in two or three seasons. According to the Shannon–Wiener index, Evenness index and richness, the bacterial diversity in gills obtained in Fall was the highest. Same richness in different tissues was found between early summer and later summer (Table 1). In the same tissue, not much difference was observed between spring and winter according to the richness index. However, in Fall season, much difference in richness was shown between the gills and other tissues (Table 1). On the other hand, bacterial diversities in richness showed little difference between digestive glands and residual tissues in Fall season (Table 1).
3.2. Phylogenetic analysis
Fig. 1. The DGGE profile of the tissue samples from retail oyster. Lanes corresponding to different tissue samples from different seasons are indicated by Roman numerals at the top (I, VI, XI: Spring; II, III, VII,VIII, XII, XIII: Summer; IV, IX, XIV: Fall; V, X, XV: Winter). The bands indicated by numbers were purified, re-amplified and subjected to sequencing.
After sequencing, a phylogenetic tree was drawn using MEGA Ver. 5.0 software. Phylogenetic analysis of 16S rRNA clone was shown in Fig. 4. The results indicated the bacterial communities in retail oyster samples were composed of Proteobacteria, Actinobacteria, Bacteroidetes, Fusobacteria, Acidobateria, Firmicutes, Nitrospirae and Verrucomicrobia (Fig. 4). From Fig. 3, members of the Proteobacteria (23/46) were dominant in oyster samples. Most of them were clustered into Vibrio sp. (12/23). This result demonstrated that Vibrio sp. was predominated in the oyster tissues. In particular, 8 sequences classified into Vibrio were only retrieved from gills, while 6 of them were discovered only in Fall sample (Figs. 2 and 4). The second predominated phylum was Bacterodetes wherein 7 sequences were assigned (Figs. 2 and 4). Except Proteobacteria, most sequences classified into other phyla were related to uncultured sequences (Fig. 4 and Supplementary Table 2).
D. Wang et al. / International Journal of Food Microbiology 173 (2014) 14–20
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Digestive glands Total bands: 25
28
22, 35 1, 2, 3, 11, 14, 15, 16, 19, 20, 21, 23, 26, 27, 30, 32, 33, 36, 37, 40, 41, 43, 44
4, 5, 9, 10, 13, 17, 18, 24, 25, 29, 34, 38, 39, 42, 45, 46
Total bands: 22
6, 7, 8, 12, 31 Gills Total bands: 45
Residual tissues Total bands: 28
Fig. 2. The bands were analyzed according the different tissues, which are numbered in the DGGE profile. 1–46: Band number labeled in DGGE gel.
Spring Total bands: 26
Summer Total bands: 31
8, 39
5,18, 29 9, 22, 31, 42
3, 36, 43, 44
1, 2, 14, 15, 16, 20, 21, 23, 26, 27, 30, 32, 33, 37, 40, 41
6, 7
Total bands: 16
4, 7, 10, 11 12, 13, 17, 19, 24 25, 28, 34, 38, 45, 46 Fall Total bands: 36
35 Winter Total bands: 23
Fig. 3. The bands were analyzed according to different seasons, are which numbered in the DGGE profile. 1–46: Band number labeled in DGGE gel.
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Fig. 4. Phylogenetic tree showing the affiliations of 16S rRNA partial sequences retrieved from this study with selected reference sequences. The clones were shown as the band number from the DGGE results. The tree was constructed by neighbor-joining method. Bootstrap values are based on 1000 replicates and shown at the nodes with more than 50% bootstrap support. The scale bar represents 5% sequence divergence.
4. Discussion In this study, the main findings were as follows: (1) bacterial diversity is high in retail oysters; (2) the highest diversity of bacteria was observed in Fall samples; (3) the gills was a promising candidate for monitoring the bacterial pathogens in retail oysters. Shanghai is located in the Yangtze River estuary. The salinity of seawater is too low to raise the shellfishes. Almost all shellfishes sold in the market were transported from other coastal provinces. It takes one or a couple of days to harvest and transport the shellfishes to the local markets in Shanghai. Before they were sold, shellfishes would be stored in market for a couple of hours to several days, which depended on the demand of customers. During the storage and transportation process, bacterial communities may shift (Chen et al., 2013; Fernandez-
Piquer et al., 2012). In addition, bacterial community in oyster was evaluated after different treatments (Azandegbe et al., 2012; Chen et al., 2013; Fernandez-Piquer et al., 2012). In this situation, we wondered what kind of profile would exist in retail shellfishes. To address this issue, the oyster was used as a model, and the community structure in its tissues was evaluated by DGGE through the whole year. For this point, understanding the seasonal dynamics and diversity of bacteria in the retail oyster will help us to improve the safety of oysters as food. Dynamics of pathogenic bacteria in oyster was also investigated during different seasons by culture-based assay (Parveen et al., 2008). The investigators focused on the cultivable bacteria and evaluated the dynamics of them. But, the bacterial diversity was different between culture-dependent and culture-independent assays (Kenneth et al., 2009; Kisand and Wikner, 2003). From those results including this
D. Wang et al. / International Journal of Food Microbiology 173 (2014) 14–20
study, more 16S rRNA genes were also amplified from uncultivable bacteria (Fernandez-Piquer et al., 2012; Green and Barnes, 2010). Although bacterial communities could be evaluated by culture-dependent methods, it was only a partial view from the whole picture of bacterial communities in oysters (Broekaert et al., 2011; Kenneth et al., 2009). It was suggested that the culture-dependent methods were not sufficient to investigate the seasonal dynamics and diversity of bacteria in oysters, especially in retail oysters. Therefore, the culture-independent method was a better way to evaluate the seasonal dynamics and the structure of the bacteria in oyster. In previous reports, the gills and digestive glands were the main tissues, which bio-accumulated pathogens including bacteria and viruses (Wang et al., 2008a, 2008b, 2010a). We expected in these main tissues, the changes of bacterial diversity were the key point. In this study, these seasonal dynamics and diversity of bacteria were investigated focusing on the main tissues. As we expected, the gills harbored a relatively diverse assemblage of phylotypes in different seasons (Figs. 1 and 2). In addition, the DGGE profile demonstrated that 31 bands were found in the gills, while 14 bands in the digestive glands and residual tissues respectively in the Fall season (Fig. 2). Our result was similar with other reports, which was investigated by different approaches (Fernandez-Piquer et al., 2012; Hernandez-Zarate and Olmos-Soto, 2006). It was described that two kinds of bacteria were found in oyster including autochthonous and allochthonous. The former may supply nutrient factors to keep oyster alive or defend its pathogens (Pujalteet al., 1999), while the latter pass through with water (Romero et al., 2002). In this study, there were 16 bands always detected in the samples in all seasons (Fig. 3). It means that 16 species were relatively permanent associated with oyster tissues. From our data, the diversity of bacteria in the gills was more complex than the autochthonous. It suggested that almost all allochthonous were in the gills, which further confirmed the previous report (Zurel et al., 2011). In other words, the allochthonous, such as foodborne pathogens, were mainly present in the gills, not in other tissues. On the other hand, from our results, the bacterial diversity in the gills was different from all other tissues (Figs. 1 and 2). Bacterial structures in the gills appeared to be highly diverse (Figs. 1 and 2). Similar results were reported that the bacterial communities in the gills were significantly different from those in guts by ARISA (Zurel et al., 2011) and FISH (Hernandez-Zarate and Olmos-Soto, 2006).Therefore, the gills were more suitable to be the target tissues for detection of foodborne pathogens from a public health standpoint. It was also a target tissue to monitor for pathogens in oysters. Because of loading capacity, 15 samples were loaded in the DGGE gel in this study. The main tissues, the gills and digestive glands, were studied to evaluate the bacterial and seasonal dynamics in retail oyster. In general, the population of bacteria in oyster was related to the environmental temperature (Gonzalez-Acosta et al., 2006; Zurel et al., 2011). Therefore, in this study, the samples were collected twice (early summer and later summer) to make sure of the bacterial diversity in retail oyster tissues. To our surprise, the bacterial diversity in summer was not the highest in different seasons as we expected. Different bacterial diversity in oyster depended on the local aquatic environment (Kenneth et al., 2009; King et al., 2012). Higher bacterial abundance was associated with higher water temperature (DePaola et al., 2003; Parveen et al., 2008).From the results of DGGE and phylogenetic analysis in this study, which exceeded our expectation, the highest bacterial diversity in retail oyster was in Fall, not in summer (Fig. 1). In Fall, the temperature was not the highest in the whole year, but the rain was much less than that in summer. Although there was less rain in spring and winter either, it was too cold for bacteria to grow. We inferred that the rain season (in summer) was one of the main reasons to limit the concentration and diversity of bacteria in aquatic farm. In this case, the rain affected the bacterial structures in oyster tissues. In general, oyster will be harvested in Fall in China, and largest quantity of oyster was consumed compared to other seasons. According to our
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results, it is a critical season for government to monitor the health risk during the oyster harvest season. In this study, 46 different 16S rRNA coding sequences were recovered and cloned (Figs. 1 and 4). In previous reports, 18 or 25 sequences were observed in the gills or individual oyster by DGGE after artificial treatment (Chen et al., 2013; Kenneth et al., 2009). More than 73 different genera-related clones in individual oysters were reported by T-RFLP (Fernandez-Piquer et al., 2012). All of these data demonstrated that high diversity was present in oysters. In addition, some of those sequences were from uncultivable bacteria (Fernandez-Piquer et al., 2012; Green and Barnes, 2010). In the last decades, all kinds of molecular assays were developed to rapidly detect these pathogens in oyster, such as PCR and real-time PCR (Liu et al., 2012; Nordstrom et al., 2007). Most methods were focused on those common pathogens, such as Vibrio parahaemolyticus and Vibrio vulnificus. However, it was hard to determine whether those uncultivable bacteria were pathogens or not. Therefore, to know those bacteria well, new media should be developed to get the pure cultures. In fact, members of the genus Vibrio are natural inhabitants of marine environments that are typically associated with oysters (Prapaiwong et al., 2009). The data demonstrated that the Proteobacteria predominated (23/46) in bacterial communities of retail oyster, which was an indicator to risk analysis. It was similar with other reports by different cultureindependent methods (Fernandez-Piquer et al., 2012; Hernandez-Zarate et al., 2006). Additionally, the seasonal variation detected in terms of diversity and density of total bacterial community demonstrated the need for a careful monitoring of oyster throughout the year. In the future, foodborne pathogenic bacteria or virus should be investigated to better understand the dynamics of these pathogens in oyster in each season. Conflict of interest None declared. Acknowledgments This work was jointly supported by the grant No. 31000063 from the National Natural Science Foundation of China, the grant No. 2012AA101601 from the Ministry of Science and Technology of China and grant from the School of Agriculture and Biology (NQN201008). We also thank Dr. Yanhong Liu from the Eastern Regional Research Center for critical reading of this manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.ijfoodmicro.2013.12.008. References Azandegbe, A., Poly, F., Andrieux-Loyer, F., Kerouel, R., Philippon, X., Nicolas, J.L., 2012. Influence of oyster culture on biogeochemistry and bacterial community structure at the sediment-water interface. FEMS Microbiol. Ecol. 82, 102–117. Broekaert, K., Heyndrickx, M., Herman, L., Devlieghere, F., Vlaemynck, G., 2011. Seafood quality analysis: molecular identification of dominant microbiota after ice storage on several general growth media. Food Microbiol. 28, 1162–1169. Chen, H., Liu, Z., Wang, M., Chen, S., Chen, T., 2013. Characterisation of the spoilage bacterial microbiota in oyster gills during storage at different temperatures. J. Sci. Food Agric. 93, 3748–3754. DePaola, A., Nordstrom, J.L., Bowers, J.C., Wells, J.G., Cook, D.W., 2003. Seasonal abundance of total and pathogenic Vibrio parahaemolyticus in Alabama oysters. Appl. Environ. Microbiol. 69, 1521–1526. Ercolini, D., 2004. PCR-DGGE fingerprinting: novel strategies for detection of microbes in food. J. Microbiol. Methods 56, 297–314. Fernandez-Piquer, J., Bowman, J.P., Ross, T., Tamplin, M.L., 2012. Molecular analysis of the bacterial communities in the live Pacific oyster (Crassostrea gigas) and the influence of postharvest temperature on its structure. J. Appl. Microbiol. 112, 1134–1143. Gonzalez-Acosta, B., Bashan, Y., Hernandez-Saavedra, N.Y., Ascencio, F., Cruz-Aguero, G., 2006. Seasonal seawater temperature as the major determinant for populations of culturable bacteria in the sediments of an intact mangrove in an arid region. FEMS Microbiol. Ecol. 55, 311–321.
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Gooch, J.A., DePaola, A., Bowers, J., Marshall, D.L., 2002. Growth and survival of Vibrio parahaemolyticus in postharvest American oysters. J. Food Prot. 65, 970–974. Green, T.J., Barnes, A.C., 2010. Bacterial diversity of the digestive gland of Sydney rock oysters, Saccostrea glomerata infected with the paramyxean parasite. Marteilia sydneyi. J. Appl. Microbiol. 109, 613–622. Hernandez-Zarate, G., Olmos-Soto, J., 2006. Identification of bacterial diversity in the oyster Crassostrea gigas by fluorescent in situ hybridization and polymerase chain reaction. J. Appl. Microbiol. 100, 664–672. Kenneth, J., La Valley, S.J., Gomez-Chiarri, Marta, Dealteris, Joseph, Rice, Michael, 2009. Bacterial community profiling of the eastern oyster (Crassostrea virginica): comparison of culture-dependent and culture-independent outcomes. J. Shellfish Res. 28, 827–835. King, G.M., Judd, C., Kuske, C.R., Smith, C., 2012. Analysis of stomach and gut microbiomes of the eastern oyster (Crassostrea virginica) from coastal Louisiana, USA. PLoS One 7, e51475. Kisand, V., Wikner, J., 2003. Combining culture-dependent and -independent methodologies for estimation of richness of estuarine bacterioplankton consuming riverine dissolved organic matter. Appl. Environ. Microbiol. 69, 3607–3616. Krebs, C.J., 1989. Ecological Methodology. Harper Collins Publishers, New York. Li, S., Sun, L., Wu, H., Hu, Z., Liu, W., Li, Y., Wen, X., 2012. The intestinal microbial diversity in mud crab (Scylla paramamosain) as determined by PCR-DGGE and clone library analysis. J. Appl. Microbiol. 113, 1341–1351. Liu, B., He, X., Chen, W., Yu, S., Shi, C., Zhou, X., Chen, J., Wang, D., Shi, X., 2012. Development of a real time PCR assay for rapid detection of Vibrio parahaemolyticus from seafood. Protein Cell 3, 204–212. Muyzer, G., de Waal, E.C., Uitterlinden, A.G., 1993. Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl. Environ. Microbiol. 59, 695–700. Nordstrom, J.L., Vickery, M.C., Blackstone, G.M., Murray, S.L., DePaola, A., 2007. Development of a multiplex real-time PCR assay with an internal amplification control for the detection of total and pathogenic Vibrio parahaemolyticus bacteria in oysters. Appl. Environ. Microbiol. 73, 5840–5847. Oguntoyinbo, F.A., Tourlomousis, P., Gasson, M.J., Narbad, A., 2011. Analysis of bacterial communities of traditional fermented West African cereal foods using culture independent methods. Int. J. Food Microbiol. 145, 205–210.
Parveen, S., Hettiarachchi, K.A., Bowers, J.C., Jones, J.L., Tamplin, M.L., McKay, R., Beatty, W., Brohawn, K., Dasilva, L.V., Depaola, A., 2008. Seasonal distribution of total and pathogenic Vibrio parahaemolyticus in Chesapeake Bay oysters and waters. Int. J. Food Microbiol. 128, 354–361. Prapaiwong, N., Wallace, R.K., Arias, C.R., 2009. Bacterial loads and microbial composition in high pressure treated oysters during storage. Int. J. Food Microbiol. 131, 145–150. Pujalte, M.J., Ortigosa, M., Macian, M.C., Garay, E., 1999. Aerobic and facultative anaerobic heterotrophic bacteria associated to Mediterranean oysters and seawater. Int. Microbiol. 2, 259–266. Romero, J., García-Varela, M., Laclette, J.P., Espejo, R.T., 2002. Bacterial 16S rRNA gene analysis revealed that bacteria related to Arcobacter spp. constitute an abundant and common component of the oyster microbiota (Tiostrea chilensis). Microb. Ecol. 44, 365–371. Thompson, J.R., Marcelino, L.A., Polz, M.F., 2005. Diversity, sources, and detection of human bacterial pathogens in the marine environment. In: Belkin, C. (Ed.), Oceans and Health: Pathogens in the Marine Environment. Springer, New York, pp. 29–68. Trabal, N., Mazon-Suastegui, J.M., Vazquez-Juarez, R., Asencio-Valle, F., MoralesBojorquez, E., Romero, J., 2012. Molecular analysis of bacterial microbiota associated with oysters (Crassostrea gigas and Crassostrea corteziensis) in different growth phases at two cultivation sites. Microb. Ecol. 64, 555–569. Wang, D., Shi, X., 2011. Distribution and detection of pathogens in shellfish–a review. Wei Sheng Wu Xue Bao 51, 1304–1309. Wang, D., Wu, Q., Kou, X., Yao, L., Zhang, J., 2008a. Distribution of norovirus in oyster tissues. J. Appl. Microbiol. 105, 1966–1972. Wang, D., Wu, Q., Yao, L., Wei, M., Kou, X., Zhang, J., 2008b. New target tissue for foodborne virus detection in oysters. Lett. Appl. Microbiol. 47, 405–409. Wang, D., Yu, S., Chen, W., Zhang, D., Shi, X., 2010a. Enumeration of Vibrio parahaemolyticus in oyster tissues following artificial contamination and depuration. Lett. Appl. Microbiol. 51, 104–108. Wang, D., Zhang, D., Chen, W., Yu, S., Shi, X., 2010b. Retention of Vibrio parahaemolyticus in oyster tissues after chlorine dioxide treatment. Int. J. Food Microbiol. 137, 76–80. Zurel, D., Benayahu, Y., Or, A., Kovacs, A., Gophna, U., 2011. Composition and dynamics of the gill microbiota of an invasive Indo-Pacific oyster in the eastern Mediterranean Sea. Environ. Microbiol. 1 13, 1467–1476.
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International Journal of Food Microbiology journal homepage: www.elsevier.com/locate/ijfoodmicro
Seasonal dynamics and diversity of bacteria in retail oyster tissues Dapeng Wang ⁎, Qian Zhang, Yan Cui, Xianming Shi MOST-USDA Joint Research Center for Food Safety & Bor Luh Food Safety Center, School of Agriculture and Biology & State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai 200240, PR China
a r t i c l e
i n f o
Article history: Received 14 October 2013 Received in revised form 6 December 2013 Accepted 8 December 2013 Available online 19 December 2013 Keywords: Retail oyster Tissues DGGE Seasonal dynamics Bacterial diversity
a b s t r a c t Oysters are one of the important vehicles for the transfer of foodborne pathogens. It was reported that bacteria could be bio-accumulated mainly in the gills and digestive glands. In artificially treated oysters, bacterial communities have been investigated by culture-independent methods after harvest. However, little information is available on the seasonal dynamics of bacterial accumulation in retail oyster tissues. In this study, retail oysters were collected from local market in different seasons. The seasonal dynamics and diversity of bacteria in oyster tissues, including the gills, digestive glands and residual tissues, were analyzed by denaturing gradient gel electrophoresis (DGGE). It was interesting that the highest bacterial diversity appeared in the Fall season, not in summer. Our results indicated that Proteobacteria was the predominant member (23/46) in oyster tissues. Our results also suggested that bacterial diversity in gills was higher than that in digestive glands and other tissues. In addition, not all the bacteria collected from surrounding water by gills were transferred to digestive glands. On the other hand, few bacteria were found in oyster tissues except in the gills. Therefore, the gills could be the best candidate target tissue for monitoring of pathogenic bacteria either to human or to oyster. © 2013 Elsevier B.V. All rights reserved.
1. Introduction Oysters are filter feeders. Because of this character, oysters bioaccumulate almost all kinds of particles, which exist in surrounding water, including bacteria and viruses. Some of them can cause infections with serious consequences either in human consumers or in oysters (Green, Barnes, 2010; Romero et al., 2002; Wang and Shi, 2011). Therefore, most literatures focused on the detection of those pathogens in oysters (Green and Barnes, 2010; Liu et al., 2012; Nordstrom et al., 2007). The microflora present in oysters depends on the environmental conditions (Kenneth et al., 2009; Prapaiwong et al., 2009).After harvest, bacterial communities, including pathogenic bacteria, in oyster would be changed dramatically even during refrigeration (Chen et al., 2013; Fernandez-Piquer et al., 2012; Gooch et al., 2002). It was reported that the total aerobic bacteria counts were over 107 CFU/g in autumn after 1 week storage at 4 °C (Prapaiwong et al., 2009). Therefore, the dynamics of bacterial diversity was a concerned issue. In general, culture-based assay was standard for detection of bacteria in oyster, but, it was not good enough to evaluate the bacterial diversity in oysters (Broekaert et al., 2011; Fernandez-Piquer et al., 2012). It was reported that less bacteria could be cultured using the currently available methods (Kenneth et al., 2009; Romero et al., 2002). Therefore, culture-independent methods were widely used to reveal the bacterial
⁎ Corresponding author at: 800 Dongchuan Rd. Minhang, Shanghai 200240, PR China, Tel.: +86 21 34206613; fax: +86 21 34206616. E-mail addresses: [email protected], [email protected] (D. Wang). 0168-1605/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ijfoodmicro.2013.12.008
communities in oyster tissues. In this field, many culture-independent methods were applied to evaluate the bacterial diversity, including denaturing gradient gel electrophoresis (DGGE), fluorescent in situ hybridization (FISH),terminal restriction fragment length polymorphism (T-RFLP) and automated ribosomal intergenic spacer analysis (ARISA) (Chen et al., 2013; Fernandez-Piquer et al., 2012; Hernandez-Zarate, Olmos-Soto, 2006; Zurel et al., 2011). In all these methods, DGGE was perhaps the most commonly used in the culture-independent fingerprinting techniques (Broekaert et al., 2011; Chen et al., 2013), and it was widely used for detection of microbes in food (Broekaert et al., 2011; Ercolini, 2004; Kenneth et al., 2009; Li et al., 2012). Recently, tissues from oysters were investigated to look for the bacterial diversities, such as live oyster (Azandegbe et al., 2012; FernandezPiquer et al., 2012; Kenneth et al., 2009), digestive glands (Green and Barnes, 2010; King et al., 2012), and the gills (Chen et al., 2013; Hernandez-Zarate et al., 2006; Zurel et al., 2011). Generally, the oysters were collected from aquatic farms and analyzed after different artificial treatments, including different storage temperature, high-pressure, quick-frozen, and infection with parasites as mentioned above. Those data boarded our knowledge on the bacterial diversity in oyster tissues. However, it was reported that oysters collected directly in the wild and laboratory-based might have different bacterial communities (Kenneth et al., 2009; Thompson et al., 2005; Trabal et al., 2012). So far, less information was available on bacterial diversities in retail oysters. To address this issue, this study investigated the seasonal dynamics and diversities of bacteria in retail oysters during transport and storage processes. This study was designed to: (1) investigate the changes of communities in different seasons; (2) reveal the diversities of bacterial communities in different retail oyster tissues. The results would provide
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more information and would be valuable as an analog of profiling on the diversities of bacteria in retail oysters. 2. Material and methods 2.1. Oyster sample treatments Oysters (Crassostrea gigas) were collected randomly from Jiangyang market in Shanghai in 2011. The oysters were collected for analysis after shipping to the market. Oysters were stored with ice in boxes. The information of samples was listed in Table 1 and treated as previously described (Wanget al., 2010a, 2010b). Briefly, oysters (n = 20) were collected randomly and opened with sterilized knives. Different tissues were dissected, including the gills, digestive glands (stomach, gut and digestive diverticula) and residual tissues (mantle and adductor muscle). Each tissue (50.0 g) was mixed with 200 ml (1:4) sterile physiological saline, and homogenized in sterile grinders. All tissues were grounded at 12,000 rpm for 1 min. After treatment, all supernatants (0.5 ml) were stored in 20% (final concentration) sterile glycerol at −80 °C until further use. 2.2. Extraction of genomic DNA The pre-treated supernatants (0.2 mL) were vortexed and centrifuged at 10,000 rpm (Eppendorf 5814D, Hamburg, Germany) for 5 min. The precipitates were washed twice with sterile physiological salt (1.0 mL) and resuspended in 0.1 mL sterile physiological salt. Genomic DNA was extracted with Allmag™ Blood Genomic DNA kit (Allrun, Shanghai, China) according to the manufacturer's protocol. Finally, genomic DNA eluted with 50 μL elution buffer was stored at −80 °C until further use.
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60 s, primer annealing at 55 °C for 45 s, and primer extension at 72 °C for 60 s; then final extension at 72 °C for 10 min. The PCR products were visualized in a 1.5% agarose gel. All PCR reactions were repeated separately for three times. To avoid bias, triplicate production of PCR was pooled, which amplified from each sample. Then, DNA was recovered with DNA Gel Extraction Kit (Omega Bio-Tek, Inc., USA) according to the manufacturer's protocol. 2.4. Denaturing gradient gel electrophoresis DGGE analysis was performed on Dcode universal mutation detection system (Bio-Rad, USA) as previously described (Muyzer et al., 1993) with minor modifications. Briefly, 10.0 μL purified PCR product was loaded to an 8% (wt/vol) polyacrylamide gel in TAE buffer. Optimal electrophoresis experiments were performed at 60 °C by using gels containing a linear 35%–55% denaturant gradient (100% corresponding to 7 mol/L urea and 40% acrylamide). Electrophoresis was performed at a constant voltage of 150 V for 5 h. Following electrophoresis, the gels were preceded for silver staining. The solutions used were 1.0% (vol/vol) ethanol plus 0.5% (vol/vol) acetic acid for fixation for 15 min; wash with filtered water (Milli-Q, Millipore) for 2 times; 0.2% silver nitrate (wt/vol) for staining for 15 min, freshly prepared stain solution containing 0.15% (vol/vol) formaldehyde; wash with filtered water for 2 times; 1.5% NaOH for developing for 5–7 min, freshly prepared developing solution containing 0.5% (vol/vol) formaldehyde; finally, 10.0% (vol/vol) ethanol and 0.5% (vol/vol) acetic acid to stop the development. The gels were digitalized and analyzed with the software package Quantity One Ver. 4.6.2 program (Bio-Rad, USA). The virtual DGGE image was performed to create a virtual DGGE image and recorded the bands in each lane. 2.5. Second amplification and sequencing
2.3. Amplification of 16S rRNA genes The V3-region of 16S rRNA genes was amplified by Polymerase Chain Reaction (PCR) in a PTC-200 thermocycler (MJ research, CA, USA). The bacterial DNA from different tissues was amplified using GC338F and 518R primers. The PCR mix consisted of 2.0 μL of genomic DNA, 2.0 U TaqE (Fermentas, Fisher Scientific, USA), 5.0 μL PCR buffer (with Mg2+), 3.2 μL of 2.5 mmol/L dNTPs, 1.0 μL of 20.0 μmol/L primers (GC338F: 5′- CCTACGGGAGGCAGCAG −3′ and 518R: 5′- ATTACCGCGG CTGCTGG-3′), the GC clamp sequence is 5′-CGCCCGGGGCGCG CCCCGG GGCGGGGCGGGGGCGCGGGGGG-3′ (Muyzer et al., 1993) and deionized water to bring up to a total reaction volume of 50.0 μL. The cycling conditions were as follows: initial denaturation at 94 °C for 5 min; 30 cycles consisting of template denaturation at 94 °C for
The bands were excised from DGGE gel and eluted in ultra pure water. DNA was recovered with Poly-Gel Extraction Kit (Omega Bio-Tek, Inc., USA) according to the manufacturer's protocol. The V3-region genes were amplified again using 338F and 518R primers (Muyzer et al., 1993). The PCR mix consisted of 2.0 μL of recovered DNA, 2.0 U TaqE (Fermentas, Fisher Scientific, USA), 5.0 μL PCR buffer (with Mg2+), 3.2 μL of 2.5 mmol/L dNTPs, 1.0 μL of 20.0 μmol/L primers and deionized water to bring up to a total reaction volume of 50.0 μL. The cycling conditions were as follows: initial denaturation at 94 °C for 4 min; 30 cycles consisting of template denaturation at 94 °C for 30 s, primer annealing at 55 °C for 30 s, and primer extension at 72 °C for 30 s; then final extension at 72 °C for 10 min. The PCR products were visualized in a 1.5% agarose gel.
Table 1 Sample information and relative species diversity (H), evenness (E), and richness (S) estimates from analysis of the DGGE band profiles of retail oyster samples. Sample
Shannon–Wiener Index (H)
Evenness (E)
Richness (S)
Seasons (Month)
Tissues
I II III IV V VI VII VIII IX X XI XII XIII XIV XV
3.019 2.924 2.815 3.407 2.982 2.904 2.986 2.886 2.657 2.907 2.874 2.886 2.923 2.650 2.992
0.938 0.960 0.925 0.943 0.951 0.926 0.952 0.920 0.938 0.915 0.904 0.920 0.932 0.917 0.929
25 21 21 37 23 23 23 23 17 24 24 23 23 18 25
Spring (Apr.) Early Summer (Jun.) Later Summer (Aug.) Fall (Nov.) Winter (Jan.) Spring (Apr.) Early Summer (Jun.) Later Summer (Aug.) Fall (Nov.) Winter (Jan.) Spring (Apr.) Early Summer (Jun.) Later Summer (Aug.) Fall (Nov.) Winter (Jan.)
Gills
Digestive glands
Residual tissues
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The isolated amplicons were recovered with DNA Gel Extraction Kit (Omega Bio-Tek, Inc., USA) and cloned into the pMD18-T (TaKaRa, Dalian, China) according to the protocol provided by the kit. Following incubation, the ligation products were transformed into Escherichia coli DH5α competent cells and plated onto Luria-Bertani (LB, OXIOD, Ltd, England) agar plates with 50 μg/mL ampicillin (Sigma, MO, USA), X-gal and isopropyl β-D-1-thiogalactopyranoside. After16 h incubation at 37 °C, the 3 white clones were selected randomly, and sequenced by Beijing Yiming Fuxing Biotechnology Co. 2.6. Statistical and phylogenetic analysis The Shannon–Wiener index and Evenness (equitability) were calculated using the equations from Krebs (Krebs., 1989). The richness was estimated as described by Oguntoyinbo (Oguntoyinbo et al., 2011). Sequences were initially compared to the available database using BLAST (Basic Local Alignment Search Tool) to determine their approximate phylogenetic affiliations and orientation. Sequences were aligned with reference 16S rRNA sequences from GenBank using the computer software program MEGA Ver. 5.0 (www.megasoftware.net). Phylogenetic trees were constructed by the neighbor-joining distance method (bootstrap =1000). 2.7. Nucleotide sequence accession numbers Nucleotide sequences obtained in this study were submitted to the NCBI GenBank database with the accession numbers of KF633394– KF633439. 3. Results 3.1. DGGE analysis of V3 regions The V3 regions of 16S rRNA from different species amplified from purified genomic DNA by PCR were separated in DGGE profiles. Total
Digestive glands
Gills I
II
III
IV
V
VI VII VIII IX
Residual tissues X
XI
XII XIII XIV XV
of 46 different bands were observed in the DGGE gel (Fig. 1). All of the bands were recovered and sequenced after second round PCR. The differences and changes in bacterial communities in oyster tissues were clearly observed (Figs. 1 and 2). There was significant difference among the three parts of tissues (Figs. 1 and 2). When the bands were analyzed according to different tissues, the results indicated that almost all bacteria were present in the gills; some were transferred from the gills to digestive glands (Fig. 2).In Fall season, bands 27 and 28 were obvious in digestive glands and residual tissues, while they were not obvious in the gills (Fig. 1).Meanwhile, not all bacteria, which were bio-accumulated by the gills, could be transferred to other tissues (Fig. 2). On the other hand, many bands were only shown in the gills, such as, bands 4, 5, 9 (Fig. 2). The bacterial diversity in the gills was highest compared with other tissues in every season (Figs. 1 and 2). In the Fall season, there were 31 bands present in the gills (lane 4 in Fig. 1), while only 14 bands were observed in residual tissues (lane 14 in Fig. 1). In digestive glands, the bacterial diversity seemed to be the same in different seasons except in the Fall season (Fig. 1). From Fig. 2, 22 bands always appeared in the different tissues. Most of them (12/22) were grouped into Proteobacteria (Supplementary Table 1). The bacterial diversity in the digestive glands (25 bands) was the lowest in all tissues samples. The highest diversity was in the gills (45 bands). There were some bands that appeared in two parts of tissues. According to time course, the bacterial diversity in Fall season was the highest in the whole year with 36 bands detected in DGGE (Fig. 3). Summer followed with 31 bands (Fig. 3), and 28 bands in early summer and 26 bands in later summer respectively (Supplementary Table 1).On the other hand, in winter, there were only 23 bands appearing in different tissues (Fig. 3). From Fig. 3, 16 bands always appeared in the different seasons. Most of them (9/16) were also grouped into Proteobacteria (Supplementary Table 1). In addition, all of the 16 bands always appeared in the different tissues (Figs. 2 and 3).The bacterial diversity in the winter season (23 bands) was the lowest in all oyster samples. The highest diversity was in the Fall season (36 bands). There were a couple of bands that appeared in two or three seasons. According to the Shannon–Wiener index, Evenness index and richness, the bacterial diversity in gills obtained in Fall was the highest. Same richness in different tissues was found between early summer and later summer (Table 1). In the same tissue, not much difference was observed between spring and winter according to the richness index. However, in Fall season, much difference in richness was shown between the gills and other tissues (Table 1). On the other hand, bacterial diversities in richness showed little difference between digestive glands and residual tissues in Fall season (Table 1).
3.2. Phylogenetic analysis
Fig. 1. The DGGE profile of the tissue samples from retail oyster. Lanes corresponding to different tissue samples from different seasons are indicated by Roman numerals at the top (I, VI, XI: Spring; II, III, VII,VIII, XII, XIII: Summer; IV, IX, XIV: Fall; V, X, XV: Winter). The bands indicated by numbers were purified, re-amplified and subjected to sequencing.
After sequencing, a phylogenetic tree was drawn using MEGA Ver. 5.0 software. Phylogenetic analysis of 16S rRNA clone was shown in Fig. 4. The results indicated the bacterial communities in retail oyster samples were composed of Proteobacteria, Actinobacteria, Bacteroidetes, Fusobacteria, Acidobateria, Firmicutes, Nitrospirae and Verrucomicrobia (Fig. 4). From Fig. 3, members of the Proteobacteria (23/46) were dominant in oyster samples. Most of them were clustered into Vibrio sp. (12/23). This result demonstrated that Vibrio sp. was predominated in the oyster tissues. In particular, 8 sequences classified into Vibrio were only retrieved from gills, while 6 of them were discovered only in Fall sample (Figs. 2 and 4). The second predominated phylum was Bacterodetes wherein 7 sequences were assigned (Figs. 2 and 4). Except Proteobacteria, most sequences classified into other phyla were related to uncultured sequences (Fig. 4 and Supplementary Table 2).
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Digestive glands Total bands: 25
28
22, 35 1, 2, 3, 11, 14, 15, 16, 19, 20, 21, 23, 26, 27, 30, 32, 33, 36, 37, 40, 41, 43, 44
4, 5, 9, 10, 13, 17, 18, 24, 25, 29, 34, 38, 39, 42, 45, 46
Total bands: 22
6, 7, 8, 12, 31 Gills Total bands: 45
Residual tissues Total bands: 28
Fig. 2. The bands were analyzed according the different tissues, which are numbered in the DGGE profile. 1–46: Band number labeled in DGGE gel.
Spring Total bands: 26
Summer Total bands: 31
8, 39
5,18, 29 9, 22, 31, 42
3, 36, 43, 44
1, 2, 14, 15, 16, 20, 21, 23, 26, 27, 30, 32, 33, 37, 40, 41
6, 7
Total bands: 16
4, 7, 10, 11 12, 13, 17, 19, 24 25, 28, 34, 38, 45, 46 Fall Total bands: 36
35 Winter Total bands: 23
Fig. 3. The bands were analyzed according to different seasons, are which numbered in the DGGE profile. 1–46: Band number labeled in DGGE gel.
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Fig. 4. Phylogenetic tree showing the affiliations of 16S rRNA partial sequences retrieved from this study with selected reference sequences. The clones were shown as the band number from the DGGE results. The tree was constructed by neighbor-joining method. Bootstrap values are based on 1000 replicates and shown at the nodes with more than 50% bootstrap support. The scale bar represents 5% sequence divergence.
4. Discussion In this study, the main findings were as follows: (1) bacterial diversity is high in retail oysters; (2) the highest diversity of bacteria was observed in Fall samples; (3) the gills was a promising candidate for monitoring the bacterial pathogens in retail oysters. Shanghai is located in the Yangtze River estuary. The salinity of seawater is too low to raise the shellfishes. Almost all shellfishes sold in the market were transported from other coastal provinces. It takes one or a couple of days to harvest and transport the shellfishes to the local markets in Shanghai. Before they were sold, shellfishes would be stored in market for a couple of hours to several days, which depended on the demand of customers. During the storage and transportation process, bacterial communities may shift (Chen et al., 2013; Fernandez-
Piquer et al., 2012). In addition, bacterial community in oyster was evaluated after different treatments (Azandegbe et al., 2012; Chen et al., 2013; Fernandez-Piquer et al., 2012). In this situation, we wondered what kind of profile would exist in retail shellfishes. To address this issue, the oyster was used as a model, and the community structure in its tissues was evaluated by DGGE through the whole year. For this point, understanding the seasonal dynamics and diversity of bacteria in the retail oyster will help us to improve the safety of oysters as food. Dynamics of pathogenic bacteria in oyster was also investigated during different seasons by culture-based assay (Parveen et al., 2008). The investigators focused on the cultivable bacteria and evaluated the dynamics of them. But, the bacterial diversity was different between culture-dependent and culture-independent assays (Kenneth et al., 2009; Kisand and Wikner, 2003). From those results including this
D. Wang et al. / International Journal of Food Microbiology 173 (2014) 14–20
study, more 16S rRNA genes were also amplified from uncultivable bacteria (Fernandez-Piquer et al., 2012; Green and Barnes, 2010). Although bacterial communities could be evaluated by culture-dependent methods, it was only a partial view from the whole picture of bacterial communities in oysters (Broekaert et al., 2011; Kenneth et al., 2009). It was suggested that the culture-dependent methods were not sufficient to investigate the seasonal dynamics and diversity of bacteria in oysters, especially in retail oysters. Therefore, the culture-independent method was a better way to evaluate the seasonal dynamics and the structure of the bacteria in oyster. In previous reports, the gills and digestive glands were the main tissues, which bio-accumulated pathogens including bacteria and viruses (Wang et al., 2008a, 2008b, 2010a). We expected in these main tissues, the changes of bacterial diversity were the key point. In this study, these seasonal dynamics and diversity of bacteria were investigated focusing on the main tissues. As we expected, the gills harbored a relatively diverse assemblage of phylotypes in different seasons (Figs. 1 and 2). In addition, the DGGE profile demonstrated that 31 bands were found in the gills, while 14 bands in the digestive glands and residual tissues respectively in the Fall season (Fig. 2). Our result was similar with other reports, which was investigated by different approaches (Fernandez-Piquer et al., 2012; Hernandez-Zarate and Olmos-Soto, 2006). It was described that two kinds of bacteria were found in oyster including autochthonous and allochthonous. The former may supply nutrient factors to keep oyster alive or defend its pathogens (Pujalteet al., 1999), while the latter pass through with water (Romero et al., 2002). In this study, there were 16 bands always detected in the samples in all seasons (Fig. 3). It means that 16 species were relatively permanent associated with oyster tissues. From our data, the diversity of bacteria in the gills was more complex than the autochthonous. It suggested that almost all allochthonous were in the gills, which further confirmed the previous report (Zurel et al., 2011). In other words, the allochthonous, such as foodborne pathogens, were mainly present in the gills, not in other tissues. On the other hand, from our results, the bacterial diversity in the gills was different from all other tissues (Figs. 1 and 2). Bacterial structures in the gills appeared to be highly diverse (Figs. 1 and 2). Similar results were reported that the bacterial communities in the gills were significantly different from those in guts by ARISA (Zurel et al., 2011) and FISH (Hernandez-Zarate and Olmos-Soto, 2006).Therefore, the gills were more suitable to be the target tissues for detection of foodborne pathogens from a public health standpoint. It was also a target tissue to monitor for pathogens in oysters. Because of loading capacity, 15 samples were loaded in the DGGE gel in this study. The main tissues, the gills and digestive glands, were studied to evaluate the bacterial and seasonal dynamics in retail oyster. In general, the population of bacteria in oyster was related to the environmental temperature (Gonzalez-Acosta et al., 2006; Zurel et al., 2011). Therefore, in this study, the samples were collected twice (early summer and later summer) to make sure of the bacterial diversity in retail oyster tissues. To our surprise, the bacterial diversity in summer was not the highest in different seasons as we expected. Different bacterial diversity in oyster depended on the local aquatic environment (Kenneth et al., 2009; King et al., 2012). Higher bacterial abundance was associated with higher water temperature (DePaola et al., 2003; Parveen et al., 2008).From the results of DGGE and phylogenetic analysis in this study, which exceeded our expectation, the highest bacterial diversity in retail oyster was in Fall, not in summer (Fig. 1). In Fall, the temperature was not the highest in the whole year, but the rain was much less than that in summer. Although there was less rain in spring and winter either, it was too cold for bacteria to grow. We inferred that the rain season (in summer) was one of the main reasons to limit the concentration and diversity of bacteria in aquatic farm. In this case, the rain affected the bacterial structures in oyster tissues. In general, oyster will be harvested in Fall in China, and largest quantity of oyster was consumed compared to other seasons. According to our
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results, it is a critical season for government to monitor the health risk during the oyster harvest season. In this study, 46 different 16S rRNA coding sequences were recovered and cloned (Figs. 1 and 4). In previous reports, 18 or 25 sequences were observed in the gills or individual oyster by DGGE after artificial treatment (Chen et al., 2013; Kenneth et al., 2009). More than 73 different genera-related clones in individual oysters were reported by T-RFLP (Fernandez-Piquer et al., 2012). All of these data demonstrated that high diversity was present in oysters. In addition, some of those sequences were from uncultivable bacteria (Fernandez-Piquer et al., 2012; Green and Barnes, 2010). In the last decades, all kinds of molecular assays were developed to rapidly detect these pathogens in oyster, such as PCR and real-time PCR (Liu et al., 2012; Nordstrom et al., 2007). Most methods were focused on those common pathogens, such as Vibrio parahaemolyticus and Vibrio vulnificus. However, it was hard to determine whether those uncultivable bacteria were pathogens or not. Therefore, to know those bacteria well, new media should be developed to get the pure cultures. In fact, members of the genus Vibrio are natural inhabitants of marine environments that are typically associated with oysters (Prapaiwong et al., 2009). The data demonstrated that the Proteobacteria predominated (23/46) in bacterial communities of retail oyster, which was an indicator to risk analysis. It was similar with other reports by different cultureindependent methods (Fernandez-Piquer et al., 2012; Hernandez-Zarate et al., 2006). Additionally, the seasonal variation detected in terms of diversity and density of total bacterial community demonstrated the need for a careful monitoring of oyster throughout the year. In the future, foodborne pathogenic bacteria or virus should be investigated to better understand the dynamics of these pathogens in oyster in each season. Conflict of interest None declared. Acknowledgments This work was jointly supported by the grant No. 31000063 from the National Natural Science Foundation of China, the grant No. 2012AA101601 from the Ministry of Science and Technology of China and grant from the School of Agriculture and Biology (NQN201008). We also thank Dr. Yanhong Liu from the Eastern Regional Research Center for critical reading of this manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.ijfoodmicro.2013.12.008. References Azandegbe, A., Poly, F., Andrieux-Loyer, F., Kerouel, R., Philippon, X., Nicolas, J.L., 2012. Influence of oyster culture on biogeochemistry and bacterial community structure at the sediment-water interface. FEMS Microbiol. Ecol. 82, 102–117. Broekaert, K., Heyndrickx, M., Herman, L., Devlieghere, F., Vlaemynck, G., 2011. Seafood quality analysis: molecular identification of dominant microbiota after ice storage on several general growth media. Food Microbiol. 28, 1162–1169. Chen, H., Liu, Z., Wang, M., Chen, S., Chen, T., 2013. Characterisation of the spoilage bacterial microbiota in oyster gills during storage at different temperatures. J. Sci. Food Agric. 93, 3748–3754. DePaola, A., Nordstrom, J.L., Bowers, J.C., Wells, J.G., Cook, D.W., 2003. Seasonal abundance of total and pathogenic Vibrio parahaemolyticus in Alabama oysters. Appl. Environ. Microbiol. 69, 1521–1526. Ercolini, D., 2004. PCR-DGGE fingerprinting: novel strategies for detection of microbes in food. J. Microbiol. Methods 56, 297–314. Fernandez-Piquer, J., Bowman, J.P., Ross, T., Tamplin, M.L., 2012. Molecular analysis of the bacterial communities in the live Pacific oyster (Crassostrea gigas) and the influence of postharvest temperature on its structure. J. Appl. Microbiol. 112, 1134–1143. Gonzalez-Acosta, B., Bashan, Y., Hernandez-Saavedra, N.Y., Ascencio, F., Cruz-Aguero, G., 2006. Seasonal seawater temperature as the major determinant for populations of culturable bacteria in the sediments of an intact mangrove in an arid region. FEMS Microbiol. Ecol. 55, 311–321.
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Gooch, J.A., DePaola, A., Bowers, J., Marshall, D.L., 2002. Growth and survival of Vibrio parahaemolyticus in postharvest American oysters. J. Food Prot. 65, 970–974. Green, T.J., Barnes, A.C., 2010. Bacterial diversity of the digestive gland of Sydney rock oysters, Saccostrea glomerata infected with the paramyxean parasite. Marteilia sydneyi. J. Appl. Microbiol. 109, 613–622. Hernandez-Zarate, G., Olmos-Soto, J., 2006. Identification of bacterial diversity in the oyster Crassostrea gigas by fluorescent in situ hybridization and polymerase chain reaction. J. Appl. Microbiol. 100, 664–672. Kenneth, J., La Valley, S.J., Gomez-Chiarri, Marta, Dealteris, Joseph, Rice, Michael, 2009. Bacterial community profiling of the eastern oyster (Crassostrea virginica): comparison of culture-dependent and culture-independent outcomes. J. Shellfish Res. 28, 827–835. King, G.M., Judd, C., Kuske, C.R., Smith, C., 2012. Analysis of stomach and gut microbiomes of the eastern oyster (Crassostrea virginica) from coastal Louisiana, USA. PLoS One 7, e51475. Kisand, V., Wikner, J., 2003. Combining culture-dependent and -independent methodologies for estimation of richness of estuarine bacterioplankton consuming riverine dissolved organic matter. Appl. Environ. Microbiol. 69, 3607–3616. Krebs, C.J., 1989. Ecological Methodology. Harper Collins Publishers, New York. Li, S., Sun, L., Wu, H., Hu, Z., Liu, W., Li, Y., Wen, X., 2012. The intestinal microbial diversity in mud crab (Scylla paramamosain) as determined by PCR-DGGE and clone library analysis. J. Appl. Microbiol. 113, 1341–1351. Liu, B., He, X., Chen, W., Yu, S., Shi, C., Zhou, X., Chen, J., Wang, D., Shi, X., 2012. Development of a real time PCR assay for rapid detection of Vibrio parahaemolyticus from seafood. Protein Cell 3, 204–212. Muyzer, G., de Waal, E.C., Uitterlinden, A.G., 1993. Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl. Environ. Microbiol. 59, 695–700. Nordstrom, J.L., Vickery, M.C., Blackstone, G.M., Murray, S.L., DePaola, A., 2007. Development of a multiplex real-time PCR assay with an internal amplification control for the detection of total and pathogenic Vibrio parahaemolyticus bacteria in oysters. Appl. Environ. Microbiol. 73, 5840–5847. Oguntoyinbo, F.A., Tourlomousis, P., Gasson, M.J., Narbad, A., 2011. Analysis of bacterial communities of traditional fermented West African cereal foods using culture independent methods. Int. J. Food Microbiol. 145, 205–210.
Parveen, S., Hettiarachchi, K.A., Bowers, J.C., Jones, J.L., Tamplin, M.L., McKay, R., Beatty, W., Brohawn, K., Dasilva, L.V., Depaola, A., 2008. Seasonal distribution of total and pathogenic Vibrio parahaemolyticus in Chesapeake Bay oysters and waters. Int. J. Food Microbiol. 128, 354–361. Prapaiwong, N., Wallace, R.K., Arias, C.R., 2009. Bacterial loads and microbial composition in high pressure treated oysters during storage. Int. J. Food Microbiol. 131, 145–150. Pujalte, M.J., Ortigosa, M., Macian, M.C., Garay, E., 1999. Aerobic and facultative anaerobic heterotrophic bacteria associated to Mediterranean oysters and seawater. Int. Microbiol. 2, 259–266. Romero, J., García-Varela, M., Laclette, J.P., Espejo, R.T., 2002. Bacterial 16S rRNA gene analysis revealed that bacteria related to Arcobacter spp. constitute an abundant and common component of the oyster microbiota (Tiostrea chilensis). Microb. Ecol. 44, 365–371. Thompson, J.R., Marcelino, L.A., Polz, M.F., 2005. Diversity, sources, and detection of human bacterial pathogens in the marine environment. In: Belkin, C. (Ed.), Oceans and Health: Pathogens in the Marine Environment. Springer, New York, pp. 29–68. Trabal, N., Mazon-Suastegui, J.M., Vazquez-Juarez, R., Asencio-Valle, F., MoralesBojorquez, E., Romero, J., 2012. Molecular analysis of bacterial microbiota associated with oysters (Crassostrea gigas and Crassostrea corteziensis) in different growth phases at two cultivation sites. Microb. Ecol. 64, 555–569. Wang, D., Shi, X., 2011. Distribution and detection of pathogens in shellfish–a review. Wei Sheng Wu Xue Bao 51, 1304–1309. Wang, D., Wu, Q., Kou, X., Yao, L., Zhang, J., 2008a. Distribution of norovirus in oyster tissues. J. Appl. Microbiol. 105, 1966–1972. Wang, D., Wu, Q., Yao, L., Wei, M., Kou, X., Zhang, J., 2008b. New target tissue for foodborne virus detection in oysters. Lett. Appl. Microbiol. 47, 405–409. Wang, D., Yu, S., Chen, W., Zhang, D., Shi, X., 2010a. Enumeration of Vibrio parahaemolyticus in oyster tissues following artificial contamination and depuration. Lett. Appl. Microbiol. 51, 104–108. Wang, D., Zhang, D., Chen, W., Yu, S., Shi, X., 2010b. Retention of Vibrio parahaemolyticus in oyster tissues after chlorine dioxide treatment. Int. J. Food Microbiol. 137, 76–80. Zurel, D., Benayahu, Y., Or, A., Kovacs, A., Gophna, U., 2011. Composition and dynamics of the gill microbiota of an invasive Indo-Pacific oyster in the eastern Mediterranean Sea. Environ. Microbiol. 1 13, 1467–1476.